#import packages
from erddapy import ERDDAP
import pandas as pd
import xarray as xr
import matplotlib.pyplot as plt
e = ERDDAP(
server="https://data.cioospacific.ca/erddap",
protocol="tabledap",
)
#set the boundary box
min_lat, max_lat = 49.28, 49.30
min_lon, max_lon = -126.62, -126.60
import folium
lon = (min_lon + max_lon) / 2
lat = (min_lat + max_lat) / 2
m = folium.Map(location=[lat, lon], tiles="OpenStreetMap", zoom_start=5)
folium.Polygon(
[(min_lat, min_lon), (max_lat, min_lon), (max_lat, max_lon), (min_lat, max_lon)],
fill=True,
).add_to(m)
m
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df = pd.read_csv(e.get_search_url(response="csv"))
df["Dataset ID"]
0 allDatasets
1 BCSOP_daily
2 BCSOP_monthly
3 IYS_NISKIN_chl_phaeo
4 IYS_2020_CTD
5 IYS_2022_TINRO_CTD
6 IYS_2019_CTD
7 PRIMED_wavebuoy
8 IOS_CTD_Profiles
9 IOS_ADCP_Moorings
10 IOS_CTD_Moorings
11 IOS_CUR_Moorings
12 IOS_BOT_Profiles
13 IYS_2019_nutrients_O2
14 IYS_2019_POM
15 DFO_MEDS_BUOYS
16 ECCC_MSC_BUOYS
17 IOS_P26_Annualized
Name: Dataset ID, dtype: object
dataset_id = "IOS_CTD_Moorings"
e.dataset_id = dataset_id
#set search variables
e.variables = [
"depth",
"time",
"latitude",
"longitude",
"sea_water_temperature",
"sea_water_practical_salinity",
"sea_water_pressure",
]
#set search criteria
e.constraints = {
"latitude>=": 49.28,
"latitude<=": 49.30,
"longitude>=": -126.62,
"longitude<=": -126.60,
}
df = e.to_pandas().dropna()
#df = e.to_pandas(index_col="time (UTC)").dropna()
df.head()
| depth (m) | time (UTC) | latitude (degrees_north) | longitude (degrees_east) | sea_water_temperature (degC) | sea_water_practical_salinity (PSS-78) | sea_water_pressure (dbar) | |
|---|---|---|---|---|---|---|---|
| 891859 | 76.847060 | 2019-08-01T00:00:00Z | 49.29 | -126.60516 | 7.9147 | 33.2059 | 77.521 |
| 891860 | 76.741010 | 2019-08-01T00:15:00Z | 49.29 | -126.60516 | 7.9138 | 33.2488 | 77.414 |
| 891861 | 76.635950 | 2019-08-01T00:30:00Z | 49.29 | -126.60516 | 7.9144 | 33.2564 | 77.308 |
| 891862 | 76.547745 | 2019-08-01T00:45:00Z | 49.29 | -126.60516 | 7.9842 | 33.1616 | 77.219 |
| 891863 | 76.495210 | 2019-08-01T01:00:00Z | 49.29 | -126.60516 | 7.8992 | 33.2524 | 77.166 |
df.shape
(236387, 7)
lat_moorings = df["latitude (degrees_north)"]
lon_moorings = df["longitude (degrees_east)"]
for i in range (0, len(df)):
folium.Marker([df.iloc[i]["latitude (degrees_north)"], df.iloc[i]["longitude (degrees_east)"]]).add_to(m)
m
#m_moorings = folium.Map(location=[lat_moorings, lon_moorings], tiles="OpenStreetMap", zoom_start=5)
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